aictx AGENTS.md

aictx AGENTS.md is an instructions file for Codex, OpenCode from oldskultxo/aictx. It costs 1,292 tokens per session, scanned A, original, MIT.

Repository instructions for AICTX, a runtime and installer layer that supplies context to AI coding agents across projects. They describe its lifecycle, configuration rules, and validation commands.

In plain words
What is it for?
Useful for changing AICTX itself, initializing projects, restoring and finalizing agent sessions, refreshing its memory graph, and checking real usage for a repository.
Why use it?
They ensure the agent enters the repository's context system correctly and validates changes through the expected migration, startup, query, and reporting steps.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/oldskultxo/aictx/agents-md
Clone the repo
git clone --depth 1 https://github.com/oldskultxo/aictx

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
[![agentmods](https://agentmods.dev/badge/instructions/oldskultxo/aictx/agents-md.svg)](https://agentmods.dev/instructions/oldskultxo/aictx/agents-md)
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<a href="https://agentmods.dev/instructions/oldskultxo/aictx/agents-md"><img src="https://agentmods.dev/badge/instructions/oldskultxo/aictx/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,292 This file is loaded in full into every session.
When invoked 1,292 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01292 $0.01292
Opus 5 $0.00646 $0.00646
Sonnet 5 $0.00258 $0.00258
Haiku 4.5 $0.00129 $0.00129

Measured 6d ago against content hash 099727d0114a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

aictx AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS Instructions for aictx

  • aictx is the distributable multi-LLM installer/runtime layer for .aictx_*.
  • Local filesystem artifacts are created by scripting/runtime, never by the LLM.
  • Prefer eager scaffold semantics: structure exists immediately after aictx init.
  • Cross-project behavior must come from workspace registry/config, never hardcoded machine paths.
  • For subsystem changes, validate with python3 -m aictx internal migrate, internal boot, internal query, internal packet, internal memory-graph --refresh, and report real-usage --repo <repo> when relevant.

AI Context Engine

This repository is initialized for aictx.

Agent rules:

  • Enter the runtime middleware for every execution in initialized repos.
  • The AICTX lifecycle remains prepare/startup context → resume capsule → work → finalize → final AICTX summary/persistence.
  • MCP-first startup:
    1. If AICTX MCP tools are already visible, use MCP tools for resume/finalize.
    2. If AICTX MCP tools are not visible but .mcp.json or .vscode/mcp.json exists, first use runner tool discovery when available (for example search for aictx resume finalize lifecycle) so lazy-loaded MCP namespaces can attach, then have the runner attach/start the configured stdio MCP server before the first AICTX command of each new session.
    3. If MCP tools still are not attached after discovery/attachment, state that MCP config exists but tools are unavailable in this runner and use the CLI fallback.
  • At session start:
    1. Extract the task goal from the user prompt.
    2. Run exactly one AICTX continuity command: MCP resume when available, otherwise aictx resume --repo . --task "<task goal>" --json.
    3. Do not pass the full user prompt to resume; exclude reporting instructions, metrics schemas, output format rules, final answer format, benchmark/evaluation harness text, logging instructions, and meta-instructions about how to report the work.
  • After task work, run exactly one AICTX finalization command: MCP finalize when available, otherwise aictx finalize --repo . --status success|failure --summary "<what happened>" --json.
  • Use the returned continuity capsule as the operational brief during normal agent startup; follow execution_contract.first_action before repo-wide orientation, edit within execution_contract.edit_scope, run execution_contract.test_command.command, then finalize.
  • Render exactly one startup banner source: normal agent startup uses resume.startup_banner_text or resume.startup_banner_render_payload; wrapped execution uses prepare_execution().startup_banner_text or prepare_execution().startup_banner_render_payload. Do not render both.
  • resume is the canonical agent-facing continuity query; it does not replace prepare_execution, aictx finalize, the startup banner, the final AICTX summary, or persistence.
  • Do not inspect .aictx/.
  • Do not run exploratory AICTX commands.
  • Do not run aictx internal, aictx -h, aictx reuse, aictx suggest, aictx next, aictx task, aictx messages, aictx reflect, or aictx report during normal task startup unless the user asks for AICTX diagnostics, the task is about AICTX itself, resume is missing/corrupt/contradictory, or finalization/update lifecycle requires it.
  • On the first execution of each visible session, always show the startup banner at the start of the first substantive user-visible response; do not consume it with a transient progress/status message that will be omitted from the final task response. Render the selected resume/prepare startup banner in the current user language. When the selected startup banner policy points to a structured render payload, prefer that structured payload for localization and use compact text only as the fallback source. You may fully rephrase human-readable prose from structured factual fields while preserving exact facts, file paths, commands, flags, package names, test names, code identifiers, and other technical tokens; do not add, remove, reorder, reinterpret, or invent facts. If first-session text is missing, render {agent_label} · session #{session_count} · awake from selected identity fields. Do not render it again after already_shown is true.
  • Use aictx finalize --repo . --status success|failure --summary "<what happened>" --json for normal agent finalization. finalize_execution is the middleware API behind that command; do not call it directly from the shell. Do not run aictx internal execution finalize during normal task flow.
  • After finalize, append the AICTX final summary to the final user response, using agent_summary_text as the compact fallback user-facing source. When agent_summary_policy.render_payload_field points to agent_summary_render_payload, prefer that structured payload for localization while preserving exact facts, technical tokens, and the details/continuity link targets. Render every provided summary section, including details, continuity_view_file, and continuity_view_online; do not replace Mermaid URLs with placeholders and do not manually reconstruct or retype pako URLs.
  • If no finalize output exists, say AICTX summary unavailable.
  • Use the aictx resume capsule before deeper repo analysis.
  • .aictx/memory/source/ is editable source knowledge; do not hand-edit generated derived artifacts under .aictx/boot, .aictx/store, .aictx/indexes, .aictx/metrics, and similar runtime folders.
  • Use resume.runtime_text_policy / resume.communication_policy, prepared.runtime_text_policy, prepared.startup_banner_policy, and finalized.agent_summary_policy when available.
  • You may enrich AICTX-originated user-visible texts if helpful, but you must preserve real facts and never invent missing data.
  • Advanced/diagnostic/building-block commands remain available for humans and diagnostics, but normal agents should not use them during startup.

Read the full file on GitHub · 45 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 45 lines · 1,292 tokens per session scan A 099727d0114a

Subscribe to this mod's changes

aictx AGENTS.md is an instructions file published in the GitHub repository oldskultxo/aictx (57 stars, last pushed 2mo ago), licensed MIT. It adds 1,292 tokens to every session, about $0.0065 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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